SIE-OBI: a streaming information extraction platform for operational business intelligence

  • Authors:
  • Malu Castellanos;Song Wang;Umeshwar Dayal;Chetan Gupta

  • Affiliations:
  • HP Labs, Palo Alto, CA, USA;HP Labs, Austin, TX, USA;HP Labs, Palo Alto, CA, USA;HP Labs, Austin, TX, USA

  • Venue:
  • Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
  • Year:
  • 2010

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Abstract

Emerging business intelligence (BI) applications aim to provide situational awareness, i.e., information about real-world events that might affect the business operations of an enterprise. For instance, an enterprise might want to know whether customers are posting positive or negative comments about a new product it has just introduced; or whether some natural disaster affects its contracted suppliers. It is difficult to develop such applications today because they require extracting and correlating facts from multiple streaming and stored data sources, typically including unstructured data, which is not well supported by BI platforms today. In this paper, we describe SIE-OBI, a system that we are developing to enable the development and execution of such applications. We describe the novel features of this system, including a declarative interface for rapidly developing such applications, and a platform for optimizing and executing the applications. We illustrate its applicability through two use cases.